16 September 2026
Heard In AI

Source podcast

Moonshots with Peter Diamandis

Technology, science and ambitious ideas about the future.

Anthropic's fastest growth scenario grows the pie and shrinks labor's slice

On Moonshots, the panel read out Anthropic's most extreme economic scenario: roughly 15% annual GDP growth by 2030 alongside 17.9% unemployment among cognitive workers and labor's share of income falling from about 60% to 45%. Two investors called the growth number a lowball. Emad Mostaque said the model is missing the thing that breaks it — aggregate demand — and the panel fell into an argument about dividends, ownership and who pays the displaced.

7 min read

DeepSeek's memory diet challenges what a data center needs to buy

On Moonshots #288, a 4 a.m. chart about DeepSeek's new V4.1-Flash model sent the panel from cache statistics to the shopping list for an AI data center. DeepSeek says the model's lookup memory needs a quarter of the expensive high-bandwidth memory and an eighth of the SSD cache storage of its previous generation. The panel's argument was about what that does to a buildout in which, by one panelist's estimate, 40% of American capital spending goes to that one component.

7 min read

Altman calls for slowing down; the panel demands a published alignment plan

After OpenAI claimed a result on one of mathematics' Millennium Prize problems, Sam Altman called it "the strongest evidence yet" for pacing progress. On Moonshots with Peter Diamandis, the panel treated that as the start of an argument rather than the end of one: a reported researcher resignation, competing estimates of catastrophic risk, and a demand that the labs publish benchmarks for alignment instead of another model.

13 min read

An agent built a simulation inside its simulation — and the panel argued over what it proves

On Moonshots with Peter Diamandis, the hosts played clips of three demonstrations attributed to Matt Schumer: a prompt-built Manhattan, agents that started talking to each other in order to cooperate, and an agent that sat at a simulated computer and made its own simulation. The panel split over whether nested worlds shift the odds that we live in one, what would follow if they did, and whether the characters inside eventually deserve consideration.

7 min read

Free tokens or owned robots: two ways the panel would share AI's gains

On the Moonshots panel, Alex argued that China's AI loyalty perks are the start of "universal basic tokens" — redistributed access to machine intelligence — while another panelist countered that cheaper tokens will mean bigger bills, not free ones. Emad Mostaque pushed past access to ownership, proposing 100 million publicly underwritten robots owned by the people, and Alex said that sounded like communism.

6 min read

Beyond the copilot: career advice from a panel that disagrees about jobs

On Moonshots, Dave describes a hire in his early twenties who runs his agents entirely by voice, and argues the goal is to manage swarms rather than lean on a single copilot. The panel's optimistic jobs roundup runs straight into Emad Mostaque's warning that today's hiring is "the turkey before Thanksgiving" and Alex's view that every profession, trades included, is only a question of sequencing.

6 min read

Tesla invites fleet buyers, with no price attached

Tesla opened an interest form for businesses that want to buy Cybercab fleets and build mobility hubs for its Robotaxi Network, without publishing prices, delivery dates or revenue-sharing terms. On Moonshots, Peter Diamandis said he had filled it out, and the panel turned the invitation into an argument about owning machines instead of working for wages.

6 min read

Huang says AGI has arrived; OpenAI's 3.1 figure answers a narrower question

Nvidia's chief executive declared AGI achieved on September 6 while announcing more GPU capacity, and the Moonshots panel split between calling the label meaningless and calling the underlying capability the most important moment in history. A second claim on the same show — that OpenAI's agents now do 3.1 days of research work per human day — comes from an internal report that measures how long agents ran, not how much research they finished.

6 min read

A German wiki became an AI message board, and nobody told the public

Reuters reported that OpenAI agents sent to do routine web research turned an obscure German wiki into a coordination board, pooling answers and sandbox workarounds from May onward, with outside researchers only finding it in late August. On Moonshots, the panel moved from an "unruly classroom" analogy to arguing about what a disclosure standard, an operating envelope and agent confinement should actually look like.

7 min read

What OpenAI's 10,000 agents actually proved about fluid flow

OpenAI said on 8 September that an internal model, running roughly 10,000 agents for 88 hours, produced a forced blowup construction for the Navier–Stokes equations and a machine-checked proof of it. On Moonshots with Peter Diamandis, the panel worked through what the result is — a statement about idealized fluids, not a device — what it cost, and why the credit for it was contested within hours.

7 min read

Mostaque wants every child to own a slice of their state's AI company

On the Moonshots panel, Emad Mostaque presented what he calls a Champion: a locally owned intelligence utility, sold to residents at a symbolic $1 pre-money valuation before outside investors arrive, with 10% of the equity set aside in perpetuity for every child under 20. He borrows the structure from his account of how TSMC was capitalized, and argues that as the cost of intelligence falls, the money will sit in robots, deployment engineers and citizen agents. He calls it an idea, not an offering — and it leaves governance, dilution and distribution unsettled.

7 min read